An Empirical Study of Cross-Language Interoperability in Replicated Data Systems

Abstract: BACKGROUND: Modern distributed systems replicate data across multiple execution sites. Business requirements and resource constraints often necessitate mixing different languages across replica sites. To facilitate the management of replicated data, modern software engineering practices integrate special-purpose replicated data libraries (RDLs) that provide read-write access to the data and ensure its synchronization. Irrespective of the implementation languages, an RDL typically uses a single language or offers bindings to a designated one. Hence, integrating existing RDLs in multilingual environments requires special-purpose code, whose software quality and performance characteristics are poorly understood. AIMS: We aim to bridge this knowledge gap to understand the software quality and performance characteristics of RDL integration in multilingual environments. METHOD: We conduct an empirical study of two key strategies for integrating RDLs in the context of multilingual replicated data systems: foreign-function interface (FFI) and a common data format (CDF); we measure and compare their respective software metrics and performance to understand their suitability for the task at hand. RESULTS: Our results reveal that adopting CDF for cross-language interaction offers software quality, latency, memory consumption, and throughput advantages. We further validate our findings by (1) creating a CDF-based RDL for mixing compiled, interpreted, and managed languages; and (2) enhancing our RDL with plug-in extensibility that enables adding functionality in a single language while maintaining integration within a multilingual environment. CONCLUSIONS: With modern distributed systems utilizing multiple languages, our findings provide novel insights for designing RDLs in multilingual replicated data systems.